Project description:MiRNA analyses of serum samples from 7 patients with colorectal cancers and 7 matched controls MiRNAs were extracted from serum by using QIAGEN miRNeasy filter column
Project description:Comparison of genomic alterations of primary colorectal cancers with liver metastases of the same patient Keywords: array CGH, colorectal cancer, colon cancer, liver metastasis 21 primary colorectal cancers and 21 matched liver metastases hybridized against sex-matched control pools
Project description:D122p53 mice (a model of D133p53 isoform) are tumour prone, have extensive inflammation and elevated serum IL-6. To investigate the role of IL-6 we crossed ∆122p53 mice with IL-6 deficient mice. Here we show that loss of IL-6 reduced JAK-STAT signalling, tumour incidence, and metastasis. We also show that D122p53 activates RhoA-ROCK signalling leading to tumour cell invasion which is IL-6 dependent and can be reduced by inhibition of JAK-STAT and RhoA-ROCK pathways. Similarly, we show that Δ133p53 activates the these pathways, resulting in invasive and migratory phenotypes, in colorectal cancer cells. Gene expression analysis of colorectal tumours showed enrichment of GPCR signalling associated with D133TP53 mRNA. Patients with elevated D133TP53 mRNA levels had a shorter disease free survival. Our results suggest that D133p53 promotes tumour invasion by activation of the JAK-STAT and RhoA-ROCK pathways and that patients whose tumours have high D133p53 may benefit from therapies targeting these pathways. In this dataset, we included the gene expression data from 35 colorectal cancers. These data were used to identify a list of enriched genesets associated with D133TP53 mRNA expression in colorectal tumours
Project description:Colorectal cancer (CRC) is one of the most prevalent and deadly cancers in the world. Despite an expanding knowledge of its molecular pathogenesis during the past two decades, robust biomarkers to enable screening, surveillance, and therapy monitoring of CRC are still lacking. In this study, we present a targeted liquid chromatography-tandem mass spectrometry-based metabolic profiling approach for identifying biomarker candidates that could enable highly sensitive and specific CRC detection using human serum samples. In this targeted approach, 158 metabolites from 25 metabolic pathways of potential significance were monitored in 234 serum samples from three groups of patients (66 CRC patients, 76 polyp patients, and 92 healthy controls). Partial least squares-discriminant analysis (PLS-DA) models were established, which proved to be powerful for distinguishing CRC patients from both healthy controls and polyp patients. Receiver operating characteristic curves generated based on these PLS-DA models showed high sensitivities (0.96 and 0.89, respectively, for differentiating CRC patients from healthy controls or polyp patients); good specificities (0.80 and 0.88), and excellent areas under the curve (0.93 and 0.95) were also obtained. Monte Carlo cross validation (MCCV) was also applied, demonstrating the robust diagnostic power of this metabolic profiling approach.
Project description:Samples were taken from colorectal cancers in surgically resected specimens in 155 colorectal cancer patients. The expression profiles were determined using Affymetrix Human Genome U133Plus 2.0 arrays. Our MSI/MSS classifier was applied to these samples. Keywords: Expression profiling by array
Project description:Comparison of expression profiles of primary colorectal cancers with liver metastases of the same patient. Additionally, expression data of normal colon and liver tissue. Abstract of publication will be included upon publication Keywords: expression profiling, colorectal cancer, colon cancer, liver metastasis, normal colonic tissue, normal liver tissue RNA of 18 primary colorectal cancers, 18 matched liver metastases, 7 normal colon epithelium samples and 5 normal liver tissue samples hybridized on Human Sentrix-6 V2 (Illumina)